Correlating proteomics and RNA-seq
Distribution of transcript abundances
## # A tibble: 2 x 10
## strain class estimate statistic p.value parameter conf.low
## <chr> <dbl> <dbl> <dbl> <dbl> <int> <dbl>
## 1 wt 2 -0.05572226 -0.2161472 0.8317849141 15 -0.5223764
## 2 wt 3 0.74836825 4.5131126 0.0003538183 16 0.4326686
## # ... with 3 more variables: conf.high <dbl>, method <fctr>,
## # alternative <fctr>## # A tibble: 1 x 9
## strain estimate statistic p.value parameter conf.low conf.high
## <chr> <dbl> <dbl> <dbl> <int> <dbl> <dbl>
## 1 wt 0.2026955 1.18908 0.2428941 33 -0.1400082 0.5020311
## # ... with 2 more variables: method <fctr>, alternative <fctr>
Correlating RNA-seq and simulated transcripts
##
## Spearman's rank correlation rho
##
## data: bar_sim_exp$avg_tpm and bar_sim_exp$transcripts
## S = 4415.9, p-value = 2.356e-07
## alternative hypothesis: true rho is not equal to 0
## sample estimates:
## rho
## 0.688802
##
## Pearson's product-moment correlation
##
## data: bar_sim$transcripts and bar_sim$proteins
## t = 30.319, df = 1558, p-value < 2.2e-16
## alternative hypothesis: true correlation is not equal to 0
## 95 percent confidence interval:
## 0.5769688 0.6394538
## sample estimates:
## cor
## 0.6091558
20x
## # A tibble: 30 x 6
## # Groups: condition, weight, time [15]
## condition weight time class cor pval
## <chr> <int> <dbl> <dbl> <dbl> <dbl>
## 1 wt 1 1200 2 0.9808074 6.924092e-10
## 2 wt 1 1200 3 0.4484130 7.102863e-02
## 3 wt 2 1200 2 0.9690893 1.178165e-08
## 4 wt 2 1200 3 0.3821410 1.300941e-01
## 5 wt 3 1200 2 0.9541847 1.209295e-07
## 6 wt 3 1200 3 0.4585705 6.411582e-02
## 7 wt 4 1200 2 0.9436479 4.091865e-07
## 8 wt 4 1200 3 0.3556315 1.612387e-01
## 9 wt 5 1200 2 0.9043404 8.976971e-06
## 10 wt 5 1200 3 0.4418357 7.578724e-02
## # ... with 20 more rows